Applied Data Analysis: Regression and Mixed Models

Understanding relationships within real-world data requires moving beyond simple correlation into structured modeling techniques. This course introduces you to modern statistical modeling, starting with core concepts and guiding you through linear regression and advanced mixed-effects frameworks for complex datasets. What you'll learn: Understand key statistical terminology, model assumptions, and core regression concepts. Build linear and multiple regression models to evaluate structured data. Analyze repeated measures and longitudinal data accurately across subject groups. Apply mixed-effects regression models to account for fixed and random variation. Interpret statistical output cleanly to draw actionable, evidence-based conclusions. Modernize your statistical workflows using structured validation practices. The learning path starts with essential definitions before exploring regression frameworks through clear written text and practical examples. Designed for beginners and working analysts looking to expand their analytical skillset, no prior advanced math is required. Enroll now to strengthen your data analysis techniques and master regression modeling.